Here Come the Teamsters: A Unionized Future for Tech Employees

By Matthew R. Lowe*

I. Introduction

Since the biggest tech giants came onto the scene, Silicon Valley has seen a tension between the companies and labor unions due to an arguable lack of employee representation.[1]  While there are numerous hypotheses for why unions have been unable to infiltrate the tech sphere, one of the most compelling explanations has been the simply technology-averse attitude of unions.  However, on March 12, 2015, Facebook agreed to a contract proposed by Teamsters Local 853 on behalf of shuttle bus drivers.[2]  The agreement could signal a major change in the landscape of employer-employee relations in the technology sector.

II. Background

A. Overview: The Changing Landscape of Employer-Employee Relations

The general employer-employee dynamic is in flux due in large part to the Obama administration.  Recently, the White House proposed a rule modifying the Employee Retirement Income Security Act (ERISA) of 1974, designed to “crack down on irresponsible behavior in today’s market for financial advice by better aligning the rules between employer-based retirement savings plans and IRAs.”[3]  In 2009, the Employee Free Choice Act was introduced into both chambers of the U.S. Congress[4] in order to remove the present right of the employer to demand an additional, separate ballot when more than half of employees have already given their signature supporting the union.[5]  Many companies have expressed serious apprehension about the possible implications of these changes.  The Teamsters union has been seeking to organize many of these companies, such as FedEx and Facebook, and the changes would make it easier for them to do so.  In response, these companies have threatened to scale back drastically in order to compensate for potential losses.[6]

B. Uber & Lyft

For quite some time, tech companies and labor unions have clashed.[7]  Until recently, none of the major tech companies had unionized employees.[8]  Much of the tension between tech companies and unions is derived from what can be construed as an adversity to technology on the part of unions.[9]  Companies like Uber and Lyft, which use mobile applications to connect passengers and cab drivers, have been under siege due to labor disputes.[10]  Currently, two lawsuits brought forth by drivers of the companies are seeking reclassification so that they are protected as employees as opposed to independent contractors.[11]  Earlier this year, the judges overseeing these matters decided that the cases would have to be decided by juries following Uber and Lyft unsuccessfully arguing that their drivers are independent contractors.[12]  If the drivers succeed in the courts, Uber and Lyft may have to change their business models entirely.

Generally, startups are able to develop more affordably and with less bureaucratic resistance when they are free to hire and maintain independent contractors.  When Uber and Lyft developed, they did so relying on and budgeting for independent contractors.[13]  Classified as employees, the drivers will be far more expensive to maintain, thus likely cutting largely into the companies’ revenue streams.  Employers “must withhold income taxes, withhold and pay Social Security and Medicare taxes, and pay unemployment tax on wage-paid” full-time employees.[14]  Further, employees would be able to organize formally.  As of 2014, Southern California Uber drivers have unofficially aligned with a local Teamsters union.[15]

C. Tech Companies and Immigration Reform

Tech companies and startups alike rely not only on independent contractors, but on foreign labor as well.  The issue with outsourcing is one that continues to be at the forefront of political discourse.[16]  Still, tech companies value high-skilled foreign labor, especially foreign engineers, whom the tech industry has continually fought to make it easier to hire.[17]  Expectedly, unions have aggressively spoken out against such efforts.  In 2013, a legislative representative for the American Federation of Labor and Congress of Industrial Organizations (AFL-CIO) stated, “The tech industry is, frankly, being greedy.  They are … blatantly trying to roll back requirements that give high-skilled American workers a fair shot at getting a job.”[18]

Recently, the Obama administration announced a new rule that would allow work permits to be provided to qualified spouses of highly skilled immigrants who are in the United States on temporary visas.[19]  This rule has been sought out by tech companies and other businesses in general.[20]  The change will primarily affect temporary workers from India and China and represents an effort both to help create jobs and to reform what has been widely acknowledged as a dysfunctional immigration system.[21]

D. Opening the Gates to Unions

In November of 2014, shuttle bus drivers under the employ of Facebook joined with the Teamsters Local 853.[22]  The alignment came amidst the drivers’ complaints of being underpaid, overworked, and unfairly compensated for time on the job.[23]  In February, the two entities formulated a union contract that was unanimously agreed upon prior to proposal.[24]  In March, Facebook accepted the terms, which included an increase in average pay “from $18 an hour to $24.50 an hour.”[25]  Other benefits include “11 paid holidays, up to five weeks of paid vacation, paid bereavement leave, paid health care for full-time workers and their families, guaranteed overtime and more.”[26]  While Facebook has set an example, it is not the only major tech company implementing improved working conditions for its employees.  Apple and Google will also be providing increased hourly pay and benefits to its shuttle drivers.[27]  Compass Transportation employees who shuttle Apple, Yahoo, eBay, Zynga, Genentech, and Amtrak have unionized recently.[28]

III. Analysis

Perhaps the shifting labor and employment landscape in Silicon Valley is indicative of a future wherein unions play a larger role in tech companies’ affairs; however, questions remain as to whether labor unions would be a good idea for developed startups and who is likely to be unionized within these startups.  As of now, drivers have been successful in either pushing forth important lawsuits, as in Uber and Lyft’s cases, or they have executed union contracts, as with Facebook.  Whether engineers, for example, will be successful in yielding similar achievements or whether they even want to do so is uncertain.

Labor unions are typically brought in to assist in improving working conditions for laborers, but startup companies are generally known for taking great care of their employees.  Google and Facebook both made Forbes’ “20 Best Places to Work in 2015” list and it is no wonder.[29]  These companies not only innovate the products of tomorrow, but they also have a hand in innovating the work environment.[30]  They are able to recruit attractive talent through “[c]ushy salaries, luxurious dining amenities, and decentralized management structures.”[31]

Even for less elite and renowned companies, labor unions could harm a natural flow that exists within the tech industry.  Specifically, there has been a longstanding reliance on freelance-type workers, especially in the development process.[32]  While this preference may signal a potentially exploitative nature on the management side of relations, it is one that has been beneficial to laborers as well.  As the tension between unions and tech companies began to crystalize as far back as 2001, Alvin Bost, a freelance web designer, told CNET that he thought “unionization would ruin the free spirit and innovation in the high-tech industry,” and went on further to note that it would be terrible for people like him.[33]  Designers, engineers, and other contract workers enjoy a level of agency that allows them, as the term “freelance” itself suggests, to move freely from company to company, thus emphasizing an important and characterizing feature of the industry: choice. Tim Colson, a software engineer, noted of working conditions that “about the only detriment [can be] the long hours” but laborers are usually “compensated in some way for the effort,” and “if a particular environment isn’t acceptable, you can simply move on.”[34]  An employment attorney in Palo Alto, Victor Schachter, said over a decade ago that “employees are going to be very reluctant (to organize) when they see the obligation of dues and the possibility of strikes and the realities of what collective bargaining is … in the end, very few, if any, of these companies will find that they have union-represented employees.”[35]  To this day, his prediction seems to hold true.

On the other hand, labor unions may be able to find a foothold with service-level workers, such as janitorial staff, who are not able to share in the wealth, prosperity, and growth of the tech industry[36] and expand from there.  As of now, there is evidence to suggest that booms in the industry benefit engineers and investors primarily, with very little trickling down to workers not at the top of the wage pyramid.[37]  Drivers, for example, seek collective bargaining for the purpose of keeping up with the rising cost of living in the Bay Area.[38]  One of Facebook’s shuttle bus drivers, Jimmy Maerina, illustrated this when he stated that he is happy to be able to live where he wants and to also “be able to put some food on the table.”[39]

IV. Conclusion

The tech industry as a whole presents a very unique platform for labor and employment relations.  This platform has paved the way for various innovations from work environment modernization to comprehensive immigration policy reform.  Still, what makes the industry particularly unique is its relationship—or lack thereof—with labor unions.  For decades, Silicon Valley has thrived with minimal union influence.  However, as the labor and employment field continues to make notable shifts, unions may be able to reformulate their tactics and develop an effective strategy for gaining a foothold in the industry through service employees.  The need for companies to provide for and maintain their service workers is acknowledged by both the workers, like drivers for Uber, Lyft, and Facebook, and management, like Facebook, Google, and Amazon.  With a greater occupation within the tech sphere, unions may be able to expand their influence, thus potentially changing not only the procedural characteristics of the industry, but perhaps entire business models as well.


*J.D., University of Illinois College of Law, expected 2017. B.A., English and Political Science, University of Massachusetts-Amherst, 2012. I would like to thank the board of the Journal of Law, Technology, and Policy for giving me the opportunity to contribute this piece. Special thanks are given to Andrew Lewis and Iman Naim for all of their advice that went into writing this piece. I also would like to thank my mentors for their ongoing and invaluable guidance: Allison Maue and Professor Paul Healey. Finally, a huge thank you always to my parents, Chrissalee and Lesly, and my sister, Victoria, for their constant encouragement.

[1] Gregory Ferenstein, Why Labor Unions And Silicon Valley Aren’t Friends, In 2 Charts, TECH CRUNCH (Jul. 29, 2013),

[2] Queenie Wong, Facebook Approves Union Contract for Shuttle Bus Drivers, SILICON BEAT (Mar. 12, 2015, 4:28 PM),

[3] Press Release, White House: Office of the Press Secretary, FACT SHEET: Middle Class Economics: Strengthening Retirement Security by Cracking Down on Backdoor Payments and Hidden Fees, WHITE HOUSE (Feb. 23, 2015), available at

[4] Steven Greenhouse, Fierce Lobbying Greets Bill to Help Workers Unionize, NY TIMES (Mar. 10, 2009),

[5] Christopher Beam, Uncivil Union: Does Card Check Kill the Secret Ballot or Not?, SLATE (Mar. 10, 2009, 7:09 PM),

[6] Alex Roth, FedEx Threatens to Cancel Jet Orders: Package-Delivery Company Puts Boeing Order in Question over Bill to Make Unionizing Easier, WALL ST. J., (last updated Mar. 25, 2009, 12:01 AM).

[7] Ferenstein, supra note 1.

[8] Id.

[9] Id.

[10] Maya Kosoff, How Two Lawsuits Could Destroy Uber and Lyft’s Business Models – and Set a Precedent for the Rest of the Sharing Economy, BUS. INSIDER (Mar. 12, 2015, 10:12 AM),

[11] Id.

[12] Id.

[13] Id.

[14] Independent Contractor (Self-Employed) or Employee?, IRS, (last updated Oct. 2, 2014).

[15] Press Release, Int’Press Release, Intr, UBER Drivers In Southern California Form Association with Teamsters Local 986 (Aug. 27, 2014), available at

[16] Chris Isidore, Rick Perry: ‘Unemployment Rate Is a Sham’, CNNMONEY (Feb. 27, 2015, 4:37 PM),

[17] Gregory Ferenstein, Major Union Calls Tech Industry news/eco for Wanting to End Hiring Wait Period for Immigrants, TECH CRUNCH (May 17, 2013),

[18] Id.

[19] Julia Preston, Rule Change Sought by Tech Firms Will Allow Some Spouses of Immigrants to Work, NY TIMES (Feb. 24, 2015),

[20] Id.

[21] Id.

[22] Kristen V. Brown, Facebook Bus Drivers Unanimously OK Union Contract, SFGATE (Feb. 23, 2015, 6:31 PM),

[23] Id.

[24] Id.

[25] Id.

[26] Wong, supra note 2.

[27] Id.

[28] Id.

[29] Kathryn Hill, The Best Places to Work in 2015, FORBES (Dec. 10, 2014, 10:43 AM),

[30] Mariana Simoes, Why Everyone Wants to Work at Big Tech Companies, BUS. INSIDER (Feb. 7, 2013, 4:12 PM),

[31] Ferenstein, supra note 1.

[32] Id.

[33] Troy Wolverton, High Technology Discovers Unions, ZD NET (Jan. 18, 2001),

[34] Id.

[35] Id.

[36] Amy B. Dean, A Rising Silicon Valley Doesn’t Lift All Boats, AL JAZEERA (Mar. 9, 2015, 1:45 AM),

[37] Id.

[38] Wong, supra note 2.

[39] Id.

Privacy and Security on the Internet

By Thomas Guzman*

I. Introduction

The Internet has changed how people get information, purchase goods, and interact with one another.  The Internet has been labeled a human right by the United Nations,[1] and Hilary Clinton has identified Internet freedom as a core value in line with freedoms of expression.[2]  Governments have struggled with questions about how to regulate the Internet.  Lately, the Internet regulatory debate has centered around privacy on the web and security on the web.  The two debates are more inextricably intertwined than may appear at first glance.  Can there be complete privacy on the Internet while maintaining enough cyber awareness to ward off potential threats?

II. Background

In a recent New York Times article, Howard E. Shrobe, a computer science professor at the Massachusetts Institute of Technology, is quoted as saying, “[t]he software we run [on the internet], the programming language we use, and the architecture of the chips we use haven’t changed much in over 30 years….[e]verything [on the internet] was built with performance, not security, in mind.”[3]

Since Edward Snowden released troves of information shedding light on the National Security Agency (NSA) data collection methods, privacy on the internet has been a much discussed topic.  Concerns center on governmental activity monitoring their own citizens’ data in the United States.

Prior to Edward Snowden’s disclosures, the Obama administration had already begun examining policy solutions to use data gathered from government entities to protect U.S. critical infrastructure for national security purposes.[4]

A. Snowden Sparks a Debate on Privacy

In 2013, a former contractor for the NSA, Edward Snowden, released thousands of documents to the media, giving the public a look into the secretive practices of the NSA.[5]  Snowden’s leaks showed the breadth and depth of NSA data collecting practices on both foreign nationals and U.S. citizens located domestically.  Snowden cited civil liberties as his primary motive for disclosing classified information.[6]  If Snowden wanted to spark a public debate on the merits of government data collection practices, he was certainly successful.

Following Snowden’s leaks, James R. Clapper, Director of National Intelligence, apologized for previously lying to Congress.  When asked if the NSA collected any type of data on millions of Americans, Clapper replied “no, sir.”[7]  U.S. District Court Judge Richard Leon said that the agency’s controversial program appears to violate the Constitution’s Fourth Amendment, which protects Americans against unreasonable searches and seizures.[8]  The program collects records of the time and phone numbers involved in every phone call made in the U.S., and allows that database to be queried for connections to suspected terrorists.  “I cannot imagine a more ‘indiscriminate’ and ‘arbitrary invasion’ than this systematic and high-tech collection and retention of personal data on virtually every single citizen for purposes of querying it and analyzing it without judicial approval,” wrote Leon, a George W. Bush appointee, in the ruling.[9]  The Supreme Court denied a writ of certiorari to hear the case.[10]

A White House-appointed review panel recommended that the government cease storing call data on hundreds of millions of Americans.[11]  President Obama acknowledged the dialogue surrounding NSA data collection and civil liberties arose at least in part due to Snowden’s disclosures.[12]

Snowden’s disclosures also raised the issue of privacy on the Internet abroad.  Brazilian President Dilma Rousseff championed legislation in her home country that has been touted as an internet bill of rights which limits the metadata that can be collected on Brazilians and promotes access to the Web.[13]

Whether or not the effects of Snowden’s disclosures are positive or negative may be one of opinion.  What cannot be undermined, however, is the rise in awareness of the scant privacy available on the Internet.  While Snowden’s actions led to a whiplash reaction to denounce the NSA’s overreach, which was compounded by the NSA falsely attributing averted terrorist attacks to the data collected, there are more considerations and factors weighing into the merits of monitoring web traffic.

B. Critical Infrastructure Concerns

In a 2013 report to Congress, the Department of Defense accused China of accessing and collecting data on U.S. diplomatic, economic and defense industries.[14]  U.S. accusations were corroborated by a report by Mandiant, a cyber-security firm, which came to similar conclusions.[15]  The accusations from Mandiant and the Defense Department demonstrated the vulnerability to U.S. national security interests against cyber-attacks.

Attempts to pass legislation to address cyber security concerns of private industry critical to national interests have stalled, especially after Snowden’s disclosures.[16]  As a result, President Obama signed an Executive Order in February 2013 that directed the Department of Homeland Security to create a national framework that reflects the increasing role of cyber security in securing physical assets.[17]  “Much of our critical infrastructure – our financial systems, power grids, pipelines, health care systems – run on networks connected to the internet, so this is a matter of public safety and of public health,” President Obama stated in January 2015 while introducing a renewed efforts to pass cyber security reform.[18]

C. Sony

In November 2014, Sony Pictures Entertainment suffered a massive cyber-attack that exposed terabytes of information including personally identifiable information (PII) of Sony employees, emails, and unreleased movies.[19]  On November 24, 2014, Sony became aware of the breach when an ominous red skull with a warning that Sony’s secrets were about to be released appeared on computers at Sony. It is unclear when Sony’s systems became compromised.[20]  A group calling itself “Guardians of Peace” took credit for the attack.  On December 19, 2014, the U.S. Federal Bureau of Investigations (FBI) concluded that North Korea was behind the attack on Sony.[21]

On December 16, 2014, Guardians of Peace, the group claiming responsibility for the hack, posted terrorist threats online directed at movie theaters if they played Sony’s motion picture “The Interview.”[22] The movie is a comedy, which includes a scene depicting the North Korean dictator Kim Jong Un being killed.  In June 2014, North Korea wrote to the Secretary General of the U.N. stating that the distribution of the movie should be regarded as an act of war.[23]

It should be noted however, that Norse, a private cyber security firm, also investigated the Sony hack and found no evidence of North Korea being responsible.[24]

Regardless of who is ultimately responsible, the cost of Sony’s hack is estimated to be upwards of $300 million.[25]

III. Analysis

“You have zero privacy anyway. Get over it,” the co-founder and chief executive of Sun Microsystems, Scott McNealy, said in response to growing concerns of consumer privacy in 1999.[26]  As abrasive as he was, McNealy’s inelegant comment seems eerily prescient sixteen years after the fact.  Every website a user visits is logged, and every post and online purchase leaves a trace of a user’s online presence.[27]  Every email sent via Google’s ubiquitous Gmail service is scanned for data for potential advertisers.[28]  With a $395 billion dollar company built on a principle of data mining and advertising, what chance does online privacy really stand?

Edward Snowden confirmed the notion that “big brother” is watching that existed long before 2012.  As early as 2004, when Facebook was a small website for college students to interact, there was an implicit understanding of the importance of protecting your online image.  There is no doubt that some information posted on the internet should be private, particularly in the case of credit card numbers used for online purchasers.  There is also clearly some information that is not private at all, such as public tweets, which are now being collected by the Library of Congress.[29]  Legal scholars will need to develop theories about all the information that falls between these two examples to determine what online information should be openly accessible and attributable and the information which should require a warrant to be admissible against a citizen.

Do the ends of protecting critical infrastructure from potentially massive disruptions, or preventing potential terrorist attacks through the means of meta-data collection justify NSA practices?  This must be considered while weighing the merits of online data privacy.

Despite the difficulties, online anonymity may be a winning bargain for privacy advocates and policy makers.  Protecting the U.S. economy and national security are goals too large to completely cease metadata collection, but with clear guidelines in place anonymity can be maintained until there is an established need to identify a person of interest.

As Dr. Shrobe stated, the Internet was built with performance in mind not security, so when the need to identify potential persons of interests arises there should be clear guidelines in place to authorize removing the veil of anonymity.[30]  The guidelines should serve as the basis for a preemptive warrant to protect against violations of citizen’s Due Process rights.  As the White House-appointed panel recommended, the government should cease storing call data on hundreds of millions of Americans – or at least cease storing data indefinitely.[31]

Sony is a private example of larger security concerns that come with an open Internet.  The costs Sony has incurred and the publicity of the attack may serve to raise awareness around cyber security.  A federal policy solution to protect industries not critical to national security interests may be a bridge too far, but private companies should begin to factor in cyber security as a cost of doing business in the Internet age, or risk being the next victim of a $300 million cyber-attack.

IV. Conclusion

The Internet has performed exceedingly well in connecting the world and delivering information quickly.  If the Internet was built with performance in mind, as Dr. Shrobe stated, it may be time to consider what the Internet should evolve into.  The Internet as a security-less means of accessing data may prove to be an economic costly proposition that is potentially detrimental to national security.  Private companies can hire cyber security firms to manage their networks and protect against potential cyber intrusions, but the threat of cyber-attacks will not be completely eliminated.  In order for the Internet to meet the challenges of the intricately connected world that it helped to create, it must evolve to become a safer medium through which businesses and governments operate.  Until then, we can remember McNealy’s words every time we log onto an Internet connection and “get over” our lack of privacy.  At least we can cross our fingers for anonymity on the web.


*J.D. Candidate, University of Illinois College of Law, expected 2017. B.A. Political Science, University of Illinois at Chicago, 2011.  I would like to thank the entire team at the Journal of Law Technology and Policy for their help on this piece.

[1] David Kravets, U.N Report Declares Internet Access a Human Right, Wired (June 3, 2011),

[2] Harichandan Arakali, Hillary Clinton Calls Internet Freedom ‘Core Value’ at Dreamforce Conference, Int’l Bus. Times (Oct. 15, 2014),

[3] Nicole Perlroth, Reinventing the Internet to Make it Safer, N.Y. Times (Dec. 2, 2014, 9:25 PM),

[4] President Barack Obama, Op-Ed., Taking the Cyberattack Threat Seriously, Wall St. J. (Jul. 19, 2012, 7:15 PM),

[5] Glenn Greenwald, Edward Snowden: The Whistleblower Behind the NSA Surveillance Revelations, Guardian (Jun. 11, 2013, 9:00 AM),

[6] U.S. Domestic Surveillance, Council on Foreign Rel. (Dec. 18, 2013),

[7] Aaron Blake, Sen. Wyden: Clapper Didn’t Give ‘Straight Answer’ on NSA Programs, Wash. Post (Jun. 11, 2013),

[8] Klayman v. Obama, 957 F. Supp. 2d 1, 42 (D.D.C. 2013).

[9] Id.

[10] Klayman v. Obama, 134 S. Ct. 1975 (2014).

[11] Richard A. Clarke, et al., Liberty and Security in a Changing World, White House 161 (Dec. 12, 2013),

[12] Office of Press Secretary,  Remarks by the President on the Review of Signals Intelligence, White House (Jan. 17, 2014, 11:15 AM),

[13] Stan Lehman, Brazil Passes an Internet “Bill of Rights”, San Jose Mercury News (Apr. 23, 2014, 10:04 AM),

[14] Office of the Secretary of Defense, Military and Security Developments Involving the People’s Republic of China 2013, Defense 36 (2013),

[15] David Sanger, David Barboza, Nicole Perlroth, Chinese Army Unit Is Seen as Tied to Hacking Against U.S., N.Y. Times (Feb. 18, 2013),

[16] Ryan Tracy, Cybersecurity Legislation Gets Renewed Push From Financial Firms, Wall St. J. (Nov. 13, 2013, 6:22 PM),

[17] Strengthening Security and Resilience of the Nation’s Critical Infrastructure, Department Homeland Security (Aug. 6, 2013),’s-critical-infrastructure.

[18] Obama Pushes Cybersecurity Legislation, N.Y. Times (Jan. 13, 2015),

[19] Todd Vanderwerff, The 2014 Sony Hacks, Explained, Vox (Jan. 20, 2015),; Andrew Wallenstein & Brent Lang, Sony’s New Movies Leak Online Following Hack Attack, Variety (Nov. 29, 2014, 6:37 PM),; Letter from Sony Pictures, toSony Pictures Entertainment Employees (Dec. 8, 2014), available at

[20] Kim Zetter, Sony Got Hacked Hard: What We Know and Don’t Know So Far, Wired (Dec. 3, 2014, 4:02 PM),

[21] FBI Statement: ‘We conclude that North Korean Government is Responsible’, Guardian (Dec. 19, 2014),

[22] Ben Child, Hackers Demand Sony Cancel Release of Kim Jong-Un-Baiting Comedy, Guardian (Dec. 9, 2014, 6:43 AM),

[23] Michelle Nichols, Bernadette Baum, North Korea Complains to U.N. About Film Starring Rogen, Franco, Reuters (Jul. 9, 2014, 1:38 PM),

[24] Tal Kopan, U.S.: No Alternate Leads in Sony Hack, Politico (Dec. 29, 2014, 7:41 PM),

[25] Annie Lowery, Sony’s Very, Very Expensive Hack, N.Y. Mag. (Dec. 16, 2014, 5:47 PM),

[26] Polly Sprenger, Sun on Privacy: ‘Get Over It’, Wired (Jan. 26, 1999),

[27] Mary Madden, et al., Digital Footprints: Online Identity Management and Search in the Age of Transparency,  Pew Internet & American Life Project, (Dec. 16, 2007, 4:00 PM),

[28] Samuel Gibbs, Gmail Does Scan All Emails, New Google Terms Clarify, Guardian (Apr. 15, 2014),

[29] Library of Congress is Archiving All Of America’s Tweets, Bus. Insider (Jan. 22, 2013),

[30] Perlroth, supra note 3.

[31] Richard A. Clarke, et al., supra note 11.

Improving Legal Scholarship with Network-Based Search Tools

By Andrew Higgins*

I. Introduction

In recent decades, network-driven data analysis has been a source of major developments and insights in neuroscience,[1] sociology,[2] and information science,[3] just to name a few of the academic fields; these tools have also been used to develop precise product marketing initiatives, more appropriate recommendations on sites such as Pandora[4] and Amazon,[5] and efficient search algorithms such as Google’s PageRank.[6] Curiously, legal research is typically not especially network-based, despite the fact that network tools such as PageRank were inspired by tools in legal analysis (especially Lexis’ Shepard Citations).[7] It is a truism among legal scholars that statutes, enforcement, precedent and interpretation are all deeply interconnected.[8] The significant role of stare decisis in contemporary legal practice makes it all the more puzzling why legal scholarship tends to be conducted in a linear or modular form. The aim of this article is to encourage a more network-theoretic approach to the identification and interpretation of legal precedent that more appropriately fits the non-modular, network structure of law.

I begin by briefly reviewing the basic concepts and tools of network analysis. Following this introduction, I highlight an important shortcoming in the most common tools for legal scholarship, and some concrete steps that could be taken to improve the methods used by lawyers and legal scholars to represent and interpret legal precedent. In particular, I argue that services such as WestlawNext and Lexis Advance could be improved if users were given more resources for going beyond simple Boolean searches. If properly implemented into the user interfaces of these services, network representations of legal precedent could make the process of searching and drawing from legal precedent more efficient, both in terms of the time taken to conduct searches and the accuracy of the results. I conclude by noting some directions for future research.

II. Background

Networks have two components: objects and relations.[9] The objects are called nodes and the relations between those objects are edges or vertices.[10] In the network represented in Figure 1, the nodes are the numbered entities (1–10) and the edges are the lines connecting those entities. Not all edges are equal. If, for example, we represented a friendship network, it would be useful to distinguish between close friends and acquaintances. To track the strength of friendship ties, we could give distinct edge weights to each (e.g., two for close friends and one for acquaintances). In Figure 1, edge weight is represented by the color of the edge, with black edges representing strong ties and gray edges weak ties. If our representation of the network were sensitive to edge weight, 9 would be spatially closer to 8 than 10.

Figure 1. An example network with ten nodes and seventeen edges.

The creation of network representations usually involves attraction and repulsion between nodes.[11] Edges between nodes act as attracting forces, with the edge weight determining the strength of the attraction.[12] In order to preserve spatial distance between nodes, this attraction is countered by a general repulsive force between all nodes. To avoid unlimited repulsion between disconnected nodes, a gravitational force pulls all nodes to the center.

The most significant properties of nodes, for present purposes, are their relational properties. Degree, a basic relational property, is equal to the number of the node’s edges.[13] In Figure 1, node 2 has a degree of four because it is related to four other nodes. Degree is a limited measure because it only considers nodes in relation to their nearest neighbors and is insensitive to the significance of the connection.[14] In a trade network, for example, it would be important to know not just which countries trade with which, but also the quantity of goods traded. To track this information, we should consider weighted degree, which assigns distinct values to each edge based on the significance of that relation, but this information is still highly limited. In analyzing a criminal or terrorist network, for example, we can learn something from the fact that A communicated with B, but we learn far more about A if we also know that B worked with C, D, and E, where these are high level figures in the illicit organization.

To track such indirect connections, we also need a measure of network centrality. Various centrality algorithms are used for different purposes, but they share an important common feature: sensitivity to a node’s position in the network as a whole.[15] Here I mention just three. The first, betweenness centrality, is a measure of how often a node occurs in the shortest path between two other nodes.[16] Nodes with higher betweenness centrality are more likely to play an essential bridge role in connecting two otherwise separate groups of nodes. In Figure 1, node 8 has the highest betweenness centrality because 9 and 10 are only related to other nodes through 8. In a network of U.S. senators, with edges defined by voting records, centrist senators would have the highest betweenness centrality because they alone bridge the divide between Republican and Democrat voting blocks. Eigenvector centrality is a measure of the importance of a node in the network as measured by its connectedness to other nodes with high Eigenvector centrality.[17] This metric is similar to the third measure of centrality, Google’s PageRank metric for determining the relevance of websites in a search, which in turn is inspired by Shepardizing.[18] The PageRank for website W is determined by considering the number of other websites with links to W, with greater weight given to linking websites that are themselves frequently linked.[19] Above, node 7 has the highest Eigenvector centrality and PageRank because it has several connections with nodes that themselves have several connections. In a citations-based network, Eigenvector centrality is a measure for the relative centrality of an author to the discussion in their area of specialty.

For present purposes, we can think of individual court opinions as nodes in the network. The most significant edges in the network are citations to previous court opinions, but one could also conceptualize the legal precedent framework with edges indicating similarity of content, geographical regions, or time periods. Whatever data are chosen as the basic structure of the network, legal scholars could, as I argue below, benefit from a network-theoretic reconceptualization of the legal terrain.

III. Analysis

Online research tools such as WestlawNext[20] and Lexis Advance[21] already have limited network-based approaches, but these services could be substantially improved by extending the user’s ability to visualize and digest the interconnected network of cases constituting current legal precedent. In this section I present several ways that these services could be enhanced. Each of the suggested changes would be relatively easy to implement and could significantly improve scholars’ and lawyers’ ability to identify the most relevant precedents. These suggestions apply to Westlaw, LexisNexis, and other similar services, but I will focus on the current user interface of WestlawNext and leave it to the reader to see how the suggestions would apply to other services.

For WestlawNext, generalized inquiry usually begins with the user providing a citation, party names, keywords, or other information into a Boolean search algorithm.[22] While this process is fairly straightforward and efficient, it has a notable shortcoming. If, for example, your aim is to find cases involving pre-verbal infants causing harm, a search for “baby” will return just those cases where “baby” appears as a keyword or within the text; but, of course, cases mentioning “infant,” “toddler,” “small child,” or “newborn” could also prove relevant. Thus, these search engines could be improved by implementing semantic network databases such that nearby terms are given some weight.

Once the user has found a relevant case, WestlawNext provides excellent network-based information in the form of KeyCite.[23] This tool allows users to immediately see a summary evaluation of how the case fits into the network of legal precedent, whether the case has been superseded, affirmed, distinguished, or received other treatments, and the significance of each related case. This information is analogous to knowing node degree, types of edges, nearest neighbors, and edge weight, but is limited in the same way as these measures of node significance. A major shortcoming of the initial search results is that users are given a list of cases, C1–Cn, each related to the queried case, C0, where C1–Cn are each provided with specific information linking it to C0, but without any further information putting these cases in a broader legal context or showing how they might directly relate to one another. This is partially remedied by the diagrammatic representation of the case history on WestlawNext, wherein users see a small set of prior cases that have been granted rehearing, had their judgment reversed, etc., but there is a great missed opportunity at this stage of the search. Along with learning how the case directly relates to prior cases, it would be valuable to have network-based representations of a greater diversity of relations and a ranking system more sensitive to a case’s position within the network of legal precedents. Researchers could benefit from visual representations of several clusters of cases relevant to their specific topics, where the edges would indicate important relations between these cases beyond the relation of explicit undermining or supporting relations. For example, one could selectively add or remove edges indicating similarity in semantic content, relevant statutes, or topics. This would be beneficial for allowing scholars to freely navigate the metaphorical legal space in a literal physical space that intuitively maps onto the conceptual distances between the various cases. When starting the research process, this would provide users with an easily digestible, unified picture of the topic highlighting the most important judgments to consider in more detail, and, for the users already familiar with the legal landscape, this service would help them identify the most important gaps in their knowledge. For most of the relevant criteria, both Westlaw and LexisNexis already possess the data, so these services could be improved simply by adding functionality to the user interface.

It would also be beneficial to use network-based measures of centrality as an indicator of the significance of cases rather than raw citation counts or merely relying on a vague sense of importance that one has inherited from peers and educators. If one wished to know the most significant landmark cases on a specific issue, one could do far worse than seeking experts’ opinions, but a quantitative measure of citation counts may be a more reliable indicator of significance than even the intuitive judgments of experts. WestlawNext provides these citation numbers, but raw citation counts can be highly misleading as a method for ranking the significance of cases because this data is not sensitive to the relative importance of the court decisions citing the case in question, and some cases have received more citations simply in virtue of the fact that they were decided earlier. By analogy, in an academic citation network, being cited by the top scholar in the field is more important than being cited by ten small players. In the same way, court decisions cited in landmark cases are more significant than those cited by several less significant cases.

To gain a more accurate representation of the most significant cases, it would be better to have a system that mirrors academic rankings like H-index[24] or Google’s algorithms for ranking websites. This could be implemented by WestlawNext and similar services by providing users with a significance score for case C that is simultaneously sensitive to all of these factors: (1) the number of cases citing and cited by C, (2) the significance of the cited cases to C and the significance of C in the court decisions citing it, and (3) the relative importance of the citing and cited cases. This sort of method has been tested by James Fowler et al., who found inward relevance (one of many measures of network centrality) was a strong predictor of future citations.[25] Given the relative success of this and similar models for accurately identifying and predicting case significance, online archives such as Westlaw could improve the relevance of their search results by using network centrality for sorting and filtering results, and they could provide more meaningful information to users by including cases’ centrality scores in the listed search results.

IV. Recommendation

The advice offered above is specifically aimed at improving the efficiency of searches for cases with legal precedent, but these tools could be used in a greater variety of contexts. I conclude by briefly suggesting a few further possibilities. Closely related to the discussion above, the method of collecting and analyzing case precedent from a network perspective could be used by legal scholars to develop highly accurate pictures of the history and future of law. For example, Fowler et al. observed that, in the cases they reviewed, the Commerce Clause was the most significant legal issue in 1955, whereas First Amendment issues had become dominant in more recent years.[26]

By identifying and tracking the trends in law over the years, researchers could develop fine-grained, data-driven overviews of the history of the law while also developing accurate models for predicting future trends. Second, scholars could use network analysis to test for possible sources of bias in judicial decisions over the years by creating and analyzing social networks showing social or communication links between judges and lawyers that correlate, in a problematic way, with judges’ rulings. Finally, similar methods could be used to compare the structures of scientific and legal citation networks to see if the legal community’s structure is relevantly similar to the structure of the sciences.


*Ph.D., Philosophy, University of Illinois.  Special thanks go to Laura Peet and Alexis Dyschkant for invaluable discussions regarding the nature and practice of law.  I also wish to thank Jonathan Waskan and Jana Diesner for providing the empirical and theoretical tools needed to approach this topic.

[1] Simon Haykin, Neural Networks: A Comprehensive Foundation (1st ed. 1994).

[2] The SAGE Handbook of Social Network Analysis (John Scott & Peter Carrington eds., 2011).

[3] Ravinda Ahuja, Thomas Magnanti, & James Orlin, Network Flows: Theory, Algorithms, and Application (1993).

[4] Pandora, (last visited Feb. 4, 2015).

[5] Amazon, (last visited Feb. 4, 2015).

[6] Ian Rogers, The Google Pagerank Algorithm and How it Works, Ian Rogers, (last visited Feb. 4, 2015).

[7] Eugene Garfield, Discovering Shepard’s Citations, WebOfStories, play/eugene.garfield/25;jsessionid=C829679D889485A4E6AF76C0C3286EF1 (last visited Feb. 4, 2015).

[8] Ronald Dworkin, Law’s Empire (1986).

[9] David Easley & Jon Kleinberg, Networks, Crowds, and Markets: Reasoning About a Highly Connected World 2 (2010).

[10] Id.

[11] Id. at 47.

[12] Id. at 53.

[13] Reinhard Diestel, Graph Theory 5 (3d ed. 2005).

[14] Easley & Kleinberg, supra note 10, at 434.

[15] Id. at 342.

[16] Id.

[17] See id. at 417. This may seem paradoxical, as Eigenvector centrality for any given node can only be determined in reference to the Eigenvector centrality of other nodes. The paradox is removed because this metric is calculated on the basis of several iterations of the algorithm.

[18] The Page Rank Algorithm, eFactory, (last visited Feb. 4, 2015).

[19] Id.

[20] WestlawNext, (last visited Feb. 4, 2015).

[21] LexisNexis, (last visited Feb. 4, 2015).

[22] WestlawNext, (last visited Feb. 4, 2015).

[23] Lexis Advance offers a similar service with Shepard’s, and its Map option mirrors WestlawNext’s case mapping function described later in the paragraph.

[24] Publish or Perish,Harzing, (last visited Feb. 4, 2015). H-index is a measure of academics’ productivity. A scholar is given a score of h where she has h papers with h publications and the remaining papers have less than or equal to h citations.

[25] James Fowler et al., Network Analysis and the Law: Measuring the Legal Importance of Precedents at the U.S. Supreme Court, 15 Pol. Analysis 324–46 (2007).

[26] Id.